JAMIA Open · 2024 · 28 citations · 34 references
ComputingHealth EducationHealth InformaticsHealth LiteracyKnowledge RepresentationNatural Language ProcessingEducational ChatbotsImmunization EducationQuestion AnsweringVaccinationVaccination For Cancer PreventionChatbotsHpv Vaccination PreventionPatient Health LiteracyVaccination LiteracyVaccination Uptake BarriersVaccination Uptake BehaviorVaccination Uptake PromotionVaccine Literacy
Objective: Human Papillomavirus (HPV) vaccine is an effective measure to prevent and control the diseases caused by HPV. However, widespread misinformation and vaccine hesitancy remain significant barriers to its uptake. This study focuses on the development of VaxBot-HPV, a chatbot aimed at improving health literacy and promoting vaccination uptake by providing information and answering questions about the HPV vaccine. Methods: We constructed the knowledge base (KB) for VaxBot-HPV, which consists of 451 documents from biomedical literature and web sources on the HPV vaccine. We extracted 202 question-answer pairs from the KB and 39 questions generated by GPT-4 for training and testing purposes. To comprehensively understand the capabilities and potential of GPT-based chatbots, 3 models were involved in this study: GPT-3.5, VaxBot-HPV, and GPT-4. The evaluation criteria included answer relevancy and faithfulness. Results: VaxBot-HPV demonstrated superior performance in answer relevancy and faithfulness compared to baselines. For test questions in KB, it achieved an answer relevancy score of 0.85 and a faithfulness score of 0.97. Similarly, it attained scores of 0.85 for answer relevancy and 0.96 for faithfulness on GPT-generated questions. Discussion: VaxBot-HPV demonstrates the effectiveness of fine-tuned large language models in healthcare, outperforming generic GPT models in accuracy and relevance. Fine-tuning mitigates hallucinations and misinformation, ensuring reliable information on HPV vaccination while allowing dynamic and tailored responses. The specific fine-tuning, which includes context in addition to question-answer pairs, enables VaxBot-HPV to provide explanations and reasoning behind its answers, enhancing transparency and user trust. Conclusions: This study underscores the importance of leveraging large language models and fine-tuning techniques in the development of chatbots for healthcare applications, with implications for improving medical education and public health communication.
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Estimates of incidence and mortality of cervical cancer in 2018: a worldwide analysis
Marc Arbyn, Elisabete Weiderpass, Laia Bruni et al. · The Lancet Global Health · 2019 · 4.1K citations · Full text
Worldwide burden of cervical cancer in 2008
Marc Arbyn, Xavier Castellsagué, Silvia de Sanjosé et al. · Annals of Oncology · 2011 · 1.1K citations
Medicine, Gynecology, Oncology +14
Review of HPV-related diseases and cancers.
Pina Brianti, De Flammineis E, Santo Raffaele Mercuri · PubMed · 2017 · 325 citations